Yung Shen (Vincent) HSIA

About Me

Hi, I'm Yung Shen (Vincent) HSIA

I am an AI Engineer and LLM Application Developer currently pursuing my Master's degree in Management Information Systems at National Chengchi University. I combine cross-disciplinary expertise in healthcare informatics, software security, and AI systems engineering to develop practical, production-grade AI solutions.

My core competencies include Large Language Model (LLM) Engineering, Formal Verification, and AI Systems Architecture Design.

In academia, I conduct research at SOSLAB (Software Security Laboratory) combining LLM applications with formal verification, exploring reliable and verifiable AI systems. I believe rigorous engineering practices are fundamental to building trustworthy AI systems.

Core Strengths

Formal Verification Expert
Combine LLM with formal verification techniques to explore reliability and safety verification of AI systems

Enterprise Experience
Accumulated production-grade application development experience at leading companies like Trend Micro, Chunghwa Telecom, and Bank SinoPac

LLM Engineering
Proficient in LLM fine-tuning, RAG, Prompt Engineering and other modern AI engineering techniques to build deployable products

Cross-Domain Background
Combine healthcare informatics, software security and AI systems engineering for unique problem-solving perspectives

3+ Years of Development

4+ Internships

2+ Academic Papers

Education

2024 – Present

Master of Science in Management Information Systems

National Chengchi University

Conducting research on integrating formal verification with LLM applications at SOSLAB (Software Security Laboratory). Research Topic: Applying Agentic LLM Architectures and SMT Solvers to the Analysis of Financial Case Law

2020 – 2024

Bachelor of Science in Healthcare Administration Medical Informatics

Kaohsiung Medical University

Interdisciplinary study of healthcare and information management, establishing a solid foundation in computer science

Technical Skills

🐍 Programming Languages

Python C++ JavaScript Go HTML/CSS

🌐 Web Frameworks

Django Flask React.js Angular.js RESTful APIs

🤖 AI/ML Frameworks

TensorFlow PyTorch LangChain LlamaIndex AutoGen

🧠 LLM Applications

LLM Fine-tuning RAG Prompt Engineering MCP Agent Design

💾 Databases

PostgreSQL MySQL MongoDB Neo4j ChromaDB

🛠️ Developer Tools

Git/GitHub Docker CI/CD Make Chainlit UI

Internship Experience

Sep 2025 – Present

AI Software Engineer Intern

GoFreight, Taipei

Designed and implemented an automated report generation pipeline using LLM to intelligently extract and analyze logistics data. Developed a customized reporting system that transforms complex business logic into accurate automated processes via Prompt Engineering, improving report generation efficiency by over 50%.

Python JavaScript Django Angular.js LangChain Prompt Engineering

Jul – Aug 2025

AI Software Engineer Intern

Trend Micro, Taipei

Designed and implemented a classifier to detect malicious MCP tool descriptions using LLM and Prompt Engineering. Developed a complete detection workflow that intercepts and blocks harmful tools, ensuring safety of automated tool execution in production environments. The system has been integrated into Trend Micro's AI security product line.

Python LLM MCP Prompt Engineering Docker CI/CD

Mar 2025 – Mar 2026

Full Stack Engineer Intern (Industry-Academia Collaboration)

Bank SinoPac, Taipei

Developed an employee performance evaluation system using React.js for the frontend and Django for the backend, with PostgreSQL as the database. Designed and implemented an algorithm integrated with an LLM to ensure each employee's evaluation report is uniquely generated.

Python JavaScript Django React.js PostgreSQL Prompt Engineering Docker

Sep 2024 – Feb 2025

GenAI Engineer Intern

Chunghwa Telecom Laboratories, Taipei

Developed and integrated the AutoGen framework for the customer service system using multi-agent collaboration architecture. Designed an Agentic RAG workflow that unified Agent and Retrieval-Augmented Generation.

Python AutoGen ChromaDB Agentic RAG MultiAgent Prompt Engineering

Jul – Aug 2024

GenAI Engineer Intern

Cathay United Bank, Taipei

Optimized the RAG ETL pipeline, building an end-to-end data extraction, transformation, and loading process.

Python RAG ChromaDB Prompt Engineering Multimodal ETL

Research Experience

Jun 2025 – Jun 2026

Research Assistant

National Chengchi University & National Taiwan University

Carbon Credit Assessment and Compliance Verification: Exploring Carbon Footprint and Cost-Effectiveness Optimization Strategies
Formalized carbon-credit regulatory frameworks into logical constraint representations and explored optimal carbon-trading strategies under legally compliant conditions. Implemented an LLM agent with self-correction capabilities to autonomously generate, verify, and refine regulatory logic, significantly reducing manual encoding effort.

Python AutoGen ChromaDB SMT Solver MultiAgent Formal Method

Jan – Dec 2025

Research Assistant

National Chengchi University & Chunghwa Telecom

The Application of AI Agent Platform to the Study of Producing Investment Analysis Reports
Applied formal methods combined with an LLM self-correction workflow to encode FSC (Financial Supervisory Commission) violation cases into logical constraint representations and identify minimally-changing compliant solutions through optimization techniques. Developed an interactive UI-based dialog framework that enables users to adjust constraints on demand.

Python AutoGen Chainlit UI SMT Solver Agentic RAG MultiAgent

Jul – Sep 2023

Research Assistant

National Cheng Kung University, Tainan

Fine-tuned the LLaMA-7B model using LoRA on the PubMedQ&A dataset. We achieved 68% accuracy and 51% F1 score during evaluation.

Python LLM Fine-tuning LoRA PyTorch Flask